Safely initiating an autonomous vehicle ride

ABSTRACT

An autonomous vehicle having a user interface and a computing system that is in communication with the user interface. The computing system may have at least one processor and at least one memory that stores computer-executable instructions. When executed by the at least one processor, the instructions may cause the at least one processor to output information through the user interface to inform the passenger of an action that the passenger needs to enact prior to the autonomous vehicle beginning to move and determine, based upon an occurrence of the action that the passenger needs to enact, whether the autonomous vehicle is permitted to begin moving.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation and claims benefit of U.S.application Ser. No. 17/825,924, filed May 26, 2022, entitled, SAFELYINITIATING AN AUTONOMOUS VEHICLE RIDE, which is a continuation andclaims the benefit of U.S. application Ser. No. 17/401,603, filed onAug. 13, 2021, entitled, SAFELY INITIATING AN AUTONOMOUS VEHICLE RIDE,now U.S. Pat. No. 11,396,857, which is a continuation and claims benefitof U.S. application Ser. No. 16/654,492, filed on Oct. 16, 2019,entitled, SAFELY INITIATING AN AUTONOMOUS VEHICLE RIDE, now U.S. Pat.No. 11,111,895 issued on Sep. 7, 2021, All of which are expresslyincorporated by reference herein in their entireties.

TECHNICAL FIELD

The present technology relates to starting an autonomous vehicle rideand more particularly to starting an autonomous vehicle ride withminimal passenger input.

BACKGROUND

An autonomous vehicle is a motorized vehicle that can navigate without ahuman driver. An exemplary autonomous vehicle includes a plurality ofsensor systems, such as, but not limited to, a camera sensor system, alidar sensor system, a radar sensor system, amongst others, wherein theautonomous vehicle operates based upon sensor signals output by thesensor systems. Specifically, the sensor signals are provided to aninternal computing system in communication with the plurality of sensorsystems, wherein a processor executes instructions based upon the sensorsignals to control a mechanical system of the autonomous vehicle, suchas a vehicle propulsion system, a braking system, or a steering system.

When an autonomous vehicle picks up a passenger, it is challenging forthe autonomous vehicle to determine when it is safe for the autonomousvehicle to begin moving and/or driving. Furthermore, without explicitactions or directions from the passenger, the autonomous vehicle findsit challenging to determine when the passenger may be prepared for theautonomous vehicle to begin moving and/or driving. Human drivers may usetheir judgement and other senses to assess actions of the passengerand/or communicate directly with the passenger to determine when thepassenger is ready for the vehicle to begin moving.

BRIEF DESCRIPTION OF THE DRAWINGS

The above-recited and other advantages and features of the presenttechnology will become apparent by reference to specific implementationsillustrated in the appended drawings. A person of ordinary skill in theart will understand that these drawings only show some examples of thepresent technology and would not limit the scope of the presenttechnology to these examples. Furthermore, the skilled artisan willappreciate the principles of the present technology as described andexplained with additional specificity and detail through the use of theaccompanying drawings in which:

FIG. 1 shows an example of an example system for operating an autonomousvehicle in accordance with some aspects of the present technology;

FIG. 2 is a flow diagram that illustrates an example process forinitiating an autonomous vehicle ride in accordance with some aspects ofthe present technology;

FIG. 3 is flow diagram that illustrates an example process for startingan autonomous vehicle ride in accordance with some aspects of thepresent technology; and

FIG. 4 shows an example of a system for implementing certain aspects ofthe present technology.

DETAILED DESCRIPTION

Various examples of the present technology are discussed in detailbelow. While specific implementations are discussed, it should beunderstood that this is done for illustration purposes only. A personskilled in the relevant art will recognize that other components andconfigurations may be used without parting from the spirit and scope ofthe present technology. For purposes of interpretation, it is to beunderstood that the usage of “and” may be used in place of “and/or.” Insome instances, well-known structures and devices are shown in blockdiagram form in order to facilitate describing one or more aspects.Further, it is to be understood that functionality that is described asbeing carried out by certain system components may be performed by moreor fewer components than shown.

In general, a vehicle used for ridesharing will come into contact withmany different passengers, many of which will have different behaviors,preferences, and belongings. In vehicles with human drivers, the humandriver can use his or her judgement to determine when the passenger hascompleted all safety requirements for the vehicle to begin moving ordriving (e.g. fastening their seatbelt, closing doors, etc.).Furthermore, the human driver can use his or her judgment or communicatedirectly with the passenger to determine when the passenger is ready forthe vehicle to begin moving or driving (e.g. the driver asks thepassenger if they're ready to go). For an autonomous vehicle having nohuman driver, it is challenging to make these determinations. Thus, thisdisclosed technology address the need in the art for an autonomousvehicle that safely initiate an autonomous vehicle ride or movement.

FIG. 1 illustrates environment 100 that includes an autonomous vehicle102 in communication with a remote computing system 150.

The autonomous vehicle 102 can navigate about roadways without a humandriver based upon sensor signals output by sensor systems 104-106 of theautonomous vehicle 102. The autonomous vehicle 102 includes a pluralityof sensor systems 104-106 (a first sensor system 104 through an Nthsensor system 106). The sensor systems 104-106 are of different typesand are arranged about the autonomous vehicle 102. For example, thefirst sensor system 104 may be a camera sensor system, and the Nthsensor system 106 may be a lidar sensor system. Other exemplary sensorsystems include radar sensor systems, global positioning system (GPS)sensor systems, inertial measurement units (IMU), infrared sensorsystems, laser sensor systems, sonar sensor systems, and the like.

The autonomous vehicle 102 further includes several mechanical systemsthat are used to effectuate appropriate motion of the autonomous vehicle102. For instance, the mechanical systems can include but are notlimited to, a vehicle propulsion system 130, a braking system 132, and asteering system 134. The vehicle propulsion system 130 may include anelectric motor, an internal combustion engine, or both. The brakingsystem 132 can include an engine brake, brake pads, actuators, and/orany other suitable componentry that is configured to assist indecelerating the autonomous vehicle 102. The steering system 134includes suitable componentry that is configured to control thedirection of movement of the autonomous vehicle 102 during navigation.

The autonomous vehicle 102 further includes a safety system 136 that caninclude various lights and signal indicators, parking brake, airbags,etc. The autonomous vehicle 102 further includes a cabin system 138 thatcan include cabin temperature control systems, in-cabin entertainmentsystems, etc.

The autonomous vehicle 102 additionally comprises an internal computingsystem 110 that is in communication with the sensor systems 104-106 andthe systems 130, 132, 134, 136, and 138. The internal computing systemincludes at least one processor and at least one memory havingcomputer-executable instructions that are executed by the processor. Thecomputer-executable instructions can make up one or more servicesresponsible for controlling the autonomous vehicle 102, communicatingwith remote computing system 150, receiving inputs from passengers orhuman co-pilots, logging metrics regarding data collected by sensorsystems 104-106 and human co-pilots, etc.

The internal computing system 110 can include a control service 112 thatis configured to control the operation of the vehicle propulsion system106, the braking system 108, the steering system 110, the safety system136, and the cabin system 138. The control service 112 receives sensorsignals from the sensor systems 104-106 as well communicates with otherservices of the internal computing system 110 to effectuate operation ofthe autonomous vehicle 102. In some embodiments, control service 112 maycarry out operations in concert one or more other systems of autonomousvehicle 102.

The internal computing system 110 can also include a constraint service114 to facilitate safe propulsion of the autonomous vehicle 102. Theconstraint service 116 includes instructions for activating a constraintbased on a rule-based restriction upon operation of the autonomousvehicle 102. For example, the constraint may be a restriction uponnavigation that is activated in accordance with protocols configured toavoid occupying the same space as other objects, abide by traffic laws,circumvent avoidance areas, etc. In some embodiments, the constraintservice can be part of the control service 112.

The internal computing system 110 can also include a communicationservice 116. The communication service can include both software andhardware elements for transmitting and receiving signals from/to theremote computing system 150. The communication service 116 is configuredto transmit information wirelessly over a network, for example, throughan antenna array that provides personal cellular (long-term evolution(LTE), 3G, 5G, etc.) communication.

In some embodiments, one or more services of the internal computingsystem 110 are configured to send and receive communications to remotecomputing system 150 for such reasons as reporting data for training andevaluating machine learning algorithms, requesting assistance fromremoting computing system or a human operator via remote computingsystem 150, software service updates, ridesharing pickup and drop offinstructions etc.

The internal computing system 110 can also include a latency service118. The latency service 118 can utilize timestamps on communications toand from the remote computing system 150 to determine if a communicationhas been received from the remote computing system 150 in time to beuseful. For example, when a service of the internal computing system 110requests feedback from remote computing system 150 on a time-sensitiveprocess, the latency service 118 can determine if a response was timelyreceived from remote computing system 150 as information can quicklybecome too stale to be actionable. When the latency service 118determines that a response has not been received within a threshold, thelatency service 118 can enable other systems of autonomous vehicle 102or a passenger to make necessary decisions or to provide the neededfeedback.

The internal computing system 110 can also include a user interfaceservice 120 that can communicate with cabin system 138 in order toprovide information or receive information to a human co-pilot or humanpassenger. In some embodiments, a human co-pilot or human passenger maybe required to evaluate and override a constraint from constraintservice 114, or the human co-pilot or human passenger may wish toprovide an instruction to the autonomous vehicle 102 regardingdestinations, requested routes, or other requested operations.

As described above, the remote computing system 150 is configured tosend/receive a signal from the autonomous vehicle 102 regardingreporting data for training and evaluating machine learning algorithms,requesting assistance from remote computing system 150 or a humanoperator via the remote computing system 150, software service updates,rideshare pickup and drop off instructions, etc.

The remote computing system 150 includes an analysis service 152 that isconfigured to receive data from autonomous vehicle 102 and analyze thedata to train or evaluate machine learning algorithms for operating theautonomous vehicle 102. The analysis service 152 can also performanalysis pertaining to data associated with one or more errors orconstraints reported by autonomous vehicle 102.

The remote computing system 150 can also include a user interfaceservice 154 configured to present metrics, video, pictures, soundsreported from the autonomous vehicle 102 to an operator of remotecomputing system 150. User interface service 154 can further receiveinput instructions from an operator that can be sent to the autonomousvehicle 102.

The remote computing system 150 can also include an instruction service156 for sending instructions regarding the operation of the autonomousvehicle 102. For example, in response to an output of the analysisservice 152 or user interface service 154, instructions service 156 canprepare instructions to one or more services of the autonomous vehicle102 or a co-pilot or passenger of the autonomous vehicle 102.

The remote computing system 150 can also include a rideshare service 158configured to interact with ridesharing application 170 operating on(potential) passenger computing devices. The rideshare service 158 canreceive requests to be picked up or dropped off from passengerridesharing app 170 and can dispatch autonomous vehicle 102 for thetrip. The rideshare service 158 can also act as an intermediary betweenthe ridesharing app 170 and the autonomous vehicle wherein a passengermight provide instructions to the autonomous vehicle to 102 go around anobstacle, change routes, honk the horn, etc.

As described herein, one aspect of the present technology is thegathering and use of data available from various sources to improvequality and experience. The present disclosure contemplates that in someinstances, this gathered data may include personal information. Thepresent disclosure contemplates that the entities involved with suchpersonal information respect and value privacy policies and practices.

FIG. 2 is a flow diagram that illustrates a process 200 for initiatingan autonomous vehicle ride.

The process 200 begins at step 202, when the autonomous vehicle 102arrives at a designated location.

At step 204, the autonomous vehicle 102 determines whether theautonomous vehicle 102 is waiting for the passenger.

If the autonomous vehicle 102 determines that the passenger requestedthe autonomous vehicle 102 through the ridesharing application 170, thenthe process proceeds to step 206. At step 206, the autonomous vehicle102 determines an identity of a passenger attempting to enter theautonomous vehicle 102. In some embodiments, the autonomous vehicle 102may use the sensor systems 104-106 to detect various physical traits ofthe passenger, including but not limited to, height, hair color, weight,approach speed towards the autonomous vehicle 102, etc. For example,prior to the passenger entering the autonomous vehicle 102, theautonomous vehicle 102 may use cameras of the sensor systems 104-106 todetect the height of the passenger as the passenger approaches theautonomous vehicle 102. As another example, after the passenger entersthe autonomous vehicle 102, the autonomous vehicle 102 may use seatsensors of the sensor systems 104-106 to determine the weight of thepassenger in the seat. In some embodiments, the autonomous vehicle 102may request and/or receive information from the passenger that mayfurther identify the passenger. For example, the autonomous vehicle 102may request the passenger to input the last four digits of their phonenumber. In some embodiments, the autonomous vehicle 102 may request orprompt the passenger for an authentication code. The authentication codemay have been sent to the autonomous vehicle 102 and the ridesharingapplication 170 of the passenger through the remote computing system150. For example, the autonomous vehicle 102 may have a keypad disposedon an exterior of the autonomous vehicle 102 to receive theauthentication code before the passenger enters the autonomous vehicle102. Similarly, the autonomous vehicle 102 may use the user interface120 to receive the authentication code after the passenger has enteredthe autonomous vehicle 102. The autonomous vehicle 102 may thenauthenticate the authentication code to determine whether theauthentication code sent to the autonomous vehicle 102 and theauthentication code sent to the ridesharing application 170 result in amatch (i.e. if the passenger is the intended passenger).

At step 208, the autonomous vehicle 102 then determines whether theidentity of the passenger attempting to enter the autonomous vehicle 102matches the identity of the passenger who requested the autonomousvehicle 102 through the ridesharing application 170. In other words, theautonomous vehicle 102 determines whether the passenger is the intendedpassenger. In some embodiments, the autonomous vehicle 102 may match thephysical traits detected above to detected physical traits of thepassenger during previous ridesharing journeys. In some embodiments,upon receipt of matching information (e.g. authentication code, lastfour digits of phone number, etc.), the autonomous vehicle 102 maydetermine that the passenger attempting to enter the autonomous vehicleis indeed the passenger who requested the autonomous vehicle 102.

If the autonomous vehicle 102 determines that the passenger attemptingto enter the autonomous vehicle 102 is the passenger who requested theautonomous vehicle 102, then the process continues to step 210. At step210, the autonomous vehicle 102 generates information and/or a greetingfor the passenger. It is further contemplated that the autonomousvehicle 102 may also customize and/or personalize the information and/orgreeting so that the passenger is aware of who the autonomous vehicle102 believes is boarding the autonomous vehicle 102 and consequentlyverify the information themselves. In other words, the autonomousvehicle 102 may output personalized information for the passenger. Insome embodiments, the autonomous vehicle 102 may also output an intendeddestination so that the passenger may also verify the intendeddestination. For example, the autonomous vehicle 102 may say “Welcomeaboard, John. We will head to the Golden Gate Bridge soon.”

If, on the other hand, the autonomous vehicle 102 determines that thepassenger attempting to enter the autonomous vehicle 102 is not thepassenger who requested the autonomous vehicle 102, then the processmoves to step 212. At step 212, the autonomous vehicle 102 remainsstopped and outputs information notifying the passenger about a mismatchbetween the passenger attempting to enter the autonomous vehicle 102 andthe passenger who requested the autonomous vehicle 102. In someembodiments, the autonomous vehicle 102 may prompt the passenger tore-enter information. For example, in embodiments that requested thelast four digits of the passenger's phone number, the autonomous vehicle102 may again prompt the passenger to enter the last four digits of thepassenger's phone number. In some embodiments, if the passengerattempting to enter the autonomous vehicle 102 inputs mismatchedinformation beyond a threshold number of instances, the autonomousvehicle 102 may enter a timeout state, in which the autonomous vehicle102 locks down and/or remains locked down so that no passenger mayaccess the autonomous vehicle 102.

Referring back to step 204, if the autonomous vehicle 102 determinesthat the passenger did not use the ridesharing application 170 torequest the autonomous vehicle (e.g. requested at a stand or hailed theautonomous vehicle), then the process 200 proceeds to step 210. At step210, as discussed above, the autonomous vehicle 102 generates a greetingfor the passenger. In some embodiments, the autonomous vehicle 102 maydetermine the identity of the passenger (e.g. like in the discussion forstep 206) and accordingly personalize the greeting as discussed above.

At step 214, the autonomous vehicle 102 determines a status of a system.The system may be one or more systems. For example, the autonomousvehicle 102 may determine whether the seatbelts are fastened and/orwhether doors to the autonomous vehicle 102 are properly closed. In someembodiments, the autonomous vehicle 102 may utilize the sensor systems104-106 to selectively check the systems. For example, the autonomousvehicle 102 may utilize seat weight sensors and/or cameras to determinewhich seats are occupied and accordingly only determine whether theseatbelts for occupied seats are fastened, instead of all seatbelts forall seats.

At step 216, the autonomous vehicle 102 determines whether theautonomous vehicle 102 is ready to start, begin moving, and/or initiatemotion. More specifically, the autonomous vehicle 102 determines whetherthe autonomous vehicle 102 is ready to initiate motion based upon thestatus of the system. For example, the autonomous vehicle 102 maydetermine that the autonomous vehicle 102 is ready to start because theseatbelts to occupied seats are fastened and all doors to the autonomousvehicle 102 are closed.

If the autonomous vehicle 102 determines that the autonomous vehicle 102is ready to start and/or begin moving, then the process 200 continues toan autonomous vehicle start sub-process 300.

If the autonomous vehicle 102 determines that the autonomous vehicle 102is not ready to start and/or begin moving, then the process 200 moves tostep 218. In step 218, the autonomous vehicle 102 prompts the passengerto enact an action. For example, the autonomous vehicle 102 may outputinformation to prompt the passenger to fasten their seatbelt. In someembodiments, the action may be providing confirmation to the autonomousvehicle 102 that the passenger is ready for the autonomous vehicle 102to initiate motion. In some embodiments, the autonomous vehicle 102 mayprompt the passenger to enact multiple actions. For example, theautonomous vehicle 102 may prompt the passenger to fasten their seatbeltand close the doors. In other words, the autonomous vehicle 102 maydetermine the statuses of multiple systems and prompt the user to enactall necessary actions at once. In some embodiments, the prompt may takea form of a message to the passenger stating that the action is apre-requisite for the autonomous vehicle 102 to initiate motion. Inother words, the autonomous vehicle 102 may output a message statingthat the passenger needs to enact the action prior to the autonomousvehicle 102 initiates motion.

At step 220, the autonomous vehicle 102 determines whether the passengerhas enacted the action. More specifically, the autonomous vehicle 102may use the sensor systems 104-106 to determine whether the passengerhas enacted the action. For example, the autonomous vehicle 102 may haverequested that the passenger stored their baggage underneath the seat.The autonomous vehicle 102 may then use a camera to detect whether thepassenger has placed the baggage underneath the seat. As anotherexample, the autonomous vehicle 102 may request the passenger to fastentheir seatbelt and accordingly determine, using seatbelt sensors,whether the passenger has fastened their seatbelt.

In either scenario, (i.e., if the autonomous vehicle 102 determines thatthe passenger has not enacted the requested action and if the autonomousvehicle 102 determines that the passenger has enacted the requestedaction), the process 200 returns to step 214, where the autonomousvehicle determines the status of the system. For example, the autonomousvehicle 102 may determine that the status of seatbelts is unfastened(i.e. step 216) and accordingly prompt the passenger to fasten theseatbelts (i.e. step 218). The autonomous vehicle 102 may then determinewhether the passenger has fastened the seatbelts (i.e. step 220). Thenthe autonomous vehicle 102 may check the statuses of other systems, suchas whether the doors are closed (i.e. step 214).

FIG. 3 is flow diagram that illustrates the autonomous vehicle startsub-process 300 for starting an autonomous vehicle drive or movement.

The sub-process starts at step 302, when the autonomous vehicle 102determines whether the autonomous vehicle 102 has determined theidentity of the passenger.

If the autonomous vehicle 102 determines that the autonomous vehicle hasdetermined the identity of the passenger, then the autonomous vehiclestart sub-process 300 continues to step 304. At step 304, the autonomousvehicle 102 determines a behavior of the passenger. More specifically,the behavior of the passenger is indicative of a readiness of thepassenger for the autonomous vehicle 102 to begin moving. In otherwords, the behavior is typically conducted when the passenger is readyand/or prepared for the autonomous vehicle 102 to begin moving. In someembodiments, the autonomous vehicle 102 may determine this behavior fromrecords of past trips taken by the passenger. The records of past tripsmay have data showing similar the passenger conducting similar behaviorprior to requesting the autonomous vehicle 102 to begin moving. Forexample, the autonomous vehicle 102 may determine that the passengertypically places a beverage in a cupholder when the passenger is readyand/or prepared for the autonomous vehicle 102 to begin moving. In someembodiments, the autonomous vehicle 102 may determine this behavior as ageneral behavior of a large number of passengers. For example, manypassengers may look up and forward after fastening their seatbelt whenthey are prepared for the autonomous vehicle 102 to begin moving. Insome embodiments, the autonomous vehicle 102 may determine more than onebehavior that is typically indicative of the readiness of the passengerfor the autonomous vehicle 102 to begin moving. Thus, the autonomousvehicle 102 may determine which of the behaviors is most stronglycorrelated to the passenger being ready for the autonomous vehicle 102to begin moving. In some embodiments, the autonomous vehicle 102 may usemultiple behaviors to determine and further confirm the passenger beingready for the autonomous vehicle 102 to begin moving.

At step 306, the autonomous vehicle 102 begins detecting for thebehavior of the passenger. The autonomous vehicle 102 may utilize thesensor systems 104-106 to detect the behavior of the passenger. Forexample, the autonomous vehicle 102 may use a cabin camera to observeand detect when the passenger fastens their seatbelt and looks up andforward.

At step 308, the autonomous vehicle 102 determines whether it hasdetected the behavior of the passenger.

If the autonomous vehicle 102 determines that it has detected thebehavior of the passenger, then the autonomous vehicle start sub-process300 continues to step 310. At step 310, the autonomous vehicle 102prompts the passenger to request the autonomous vehicle 102 to beginmoving or ask the passenger whether the passenger is ready for theautonomous vehicle 102 to begin moving. For example, the autonomousvehicle 102 may prompt the passenger to press the physical Start Ridebutton or to say “Start the ride.” As another example, the autonomousvehicle 102 may ask “Are you ready to start the ride?” for which theautonomous vehicle 102 may wait to receive a response. Afterwards, theautonomous vehicle start sub-process 300 continues to step 312, wherethe autonomous vehicle 102 determines whether it has received therequest.

Referring back to step 308, if the autonomous vehicle 102 determinesthat it has not detected the behavior of the passenger, then theautonomous vehicle start sub-process 300 continues directly to step 312.At step 312, the autonomous vehicle 102 determines whether it hasreceived a request to begin moving. For example, the passenger mayexplicitly say “Start the ride” or press a physical Start Ride button.

If the autonomous vehicle 102 has determined that it has not received arequest to begin moving, then the autonomous vehicle start sub-process300 continues to returns to step 306.

If the autonomous vehicle 102 has determined that it has received arequest to begin moving, the autonomous vehicle start sub-process 300also continues to step 314. At step 314, the autonomous vehicle 102controls the autonomous vehicle 102 to initiate motion. In someembodiments, the autonomous vehicle 102 may also notify the passengerthat the autonomous vehicle 102 will begin moving.

Referring back to Step 302, if the autonomous vehicle determines that ithas not determined the identity of the passenger, then the autonomousvehicle start sub-process 300 continues to step 316. At step 316, theautonomous vehicle waits until it receives a request for the autonomousvehicle to begin moving. Like the request in step 308, the request maybe the passenger explicitly saying “Start the ride” or pressing aphysical Start Ride button. In some embodiments, the autonomous vehicle102 may observe and detect for general behavioral indicators that aperson is settled in and ready to have the autonomous vehicle 102initiate motion. After the autonomous vehicle 102 detects the generalbehavioral indicators, the autonomous vehicle 102 may ask or prompt thepassenger if they are ready for the autonomous vehicle 102 to initiatemotion.

At step 318, the autonomous vehicle 102 determines whether it hasreceived the request to begin moving.

If the autonomous vehicle 102 determines that it has not received therequest to begin moving, the autonomous vehicle start sub-process 300returns to step 316, where it waits until it receives a request for theautonomous vehicle 102 to begin moving.

If the autonomous vehicle 102 determines that it has received therequest to begin moving, the autonomous vehicle start sub-process 300continues to step 314, as defined above.

The order or sequence of the above process and sub-process is merely forexplanatory purposes. One of ordinary skill in the art will understandand appreciate that many of the steps may be interchangeable and/orimplemented in different points in time. For example, steps 308 and 310may occur concurrently or in reverse order to yield a similar result.

It is further contemplated that the process 200 and the autonomousvehicle start sub-process 300 may be utilized multiple times formultiple passengers. For example, after the autonomous vehicle 102 picksup a passenger and embarks on a first journey, a second passenger mayrequest the autonomous vehicle 102 to join a second journey similar tothe first journey. Thus, the autonomous vehicle 102 may also pick up thesecond passenger during the first journey. In these situations, theautonomous vehicle 102 may display a notification through the userinterface 120 to notify the passenger that the autonomous vehicle willpick up a second passenger. The autonomous vehicle 102 may then stop topick up the second passenger. Then, the autonomous vehicle 102 mayconduct process 200 and sub-process 300 to output information to thesecond passenger about a second action that the second passenger needsto enact. Again, the autonomous vehicle 102 may then detect using thesensor systems 104-106 the second action that the second passenger needsto enact. After detecting the occurrence of the second action performedby the second passenger, the autonomous vehicle 102 may then control theautonomous vehicle 102 to begin moving.

In some embodiments, the autonomous vehicle 102 may determine aprojected amount of time the autonomous vehicle 102 is permitted toremain stationary. If the autonomous vehicle 102 determines that theprojected amount of time the autonomous vehicle 102 is permitted toremain stationary is a short amount of time, then the autonomous vehicle102 may initiate a rushed start so that the autonomous vehicle 102 doesnot exceed the projected amount of time the autonomous vehicle 102 ispermitted to remain stationary. More specifically, the rushed start maydetect the occurrence of the action(s) that the passenger needs toenact, but may be waiting for active or implied consent from the user.In some embodiments, the autonomous vehicle 102 may determine that,based on a profile of the user, the user has agreed to allow theautonomous vehicle 102 to begin moving as soon as all safety actionshave been enacted. In other embodiments, the autonomous vehicle 102 maytransmit an acoustic signal (e.g. “when you are ready to go, say‘ready’”) to the user requesting permission to begin moving, and mayreceive an indication that the user is ready via an in-car display or amicrophone. In some embodiments, the autonomous vehicle 102 may alsooutput additional information after the autonomous vehicle 102 beginsmoving. For example, the autonomous vehicle 102 may state “Sorry for therushed start, there is a strict time limit for remaining stationary inthis area. We are now on our way to the Golden Gate Bridge.”

FIG. 4 shows an example of computing system 400, which can be forexample any computing device making up internal computing system 110,remote computing system 150, (potential) passenger device executingrideshare app 170, or any component thereof in which the components ofthe system are in communication with each other using connection 405.Connection 405 can be a physical connection via a bus, or a directconnection into processor 410, such as in a chipset architecture.Connection 405 can also be a virtual connection, networked connection,or logical connection.

In some embodiments, computing system 400 is a distributed system inwhich the functions described in this disclosure can be distributedwithin a datacenter, multiple data centers, a peer network, etc. In someembodiments, one or more of the described system components representsmany such components each performing some or all of the function forwhich the component is described. In some embodiments, the componentscan be physical or virtual devices.

Example system 400 includes at least one processing unit (CPU orprocessor) 410 and connection 405 that couples various system componentsincluding system memory 415, such as read-only memory (ROM) 420 andrandom access memory (RAM) 425 to processor 410. Computing system 400can include a cache of high-speed memory 412 connected directly with, inclose proximity to, or integrated as part of processor 410.

Processor 410 can include any general purpose processor and a hardwareservice or software service, such as services 432, 434, and 436 storedin storage device 430, configured to control processor 410 as well as aspecial-purpose processor where software instructions are incorporatedinto the actual processor design. Processor 410 may essentially be acompletely self-contained computing system, containing multiple cores orprocessors, a bus, memory controller, cache, etc. A multi-core processormay be symmetric or asymmetric.

To enable user interaction, computing system 400 includes an inputdevice 445, which can represent any number of input mechanisms, such asa microphone for speech, a touch-sensitive screen for gesture orgraphical input, keyboard, mouse, motion input, speech, etc. Computingsystem 400 can also include output device 435, which can be one or moreof a number of output mechanisms known to those of skill in the art. Insome instances, multimodal systems can enable a user to provide multipletypes of input/output to communicate with computing system 400.Computing system 400 can include communications interface 440, which cangenerally govern and manage the user input and system output. There isno restriction on operating on any particular hardware arrangement, andtherefore the basic features here may easily be substituted for improvedhardware or firmware arrangements as they are developed.

Storage device 430 can be a non-volatile memory device and can be a harddisk or other types of computer readable media which can store data thatare accessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices, digital versatile disks, cartridges,random access memories (RAMs), read-only memory (ROM), and/or somecombination of these devices.

The storage device 430 can include software services, servers, services,etc., that when the code that defines such software is executed by theprocessor 410, it causes the system to perform a function. In someembodiments, a hardware service that performs a particular function caninclude the software component stored in a computer-readable medium inconnection with the necessary hardware components, such as processor410, connection 405, output device 435, etc., to carry out the function.

For clarity of explanation, in some instances, the present technologymay be presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

Any of the steps, operations, functions, or processes described hereinmay be performed or implemented by a combination of hardware andsoftware services or services, alone or in combination with otherdevices. In some embodiments, a service can be software that resides inmemory of a client device and/or one or more servers of a contentmanagement system and perform one or more functions when a processorexecutes the software associated with the service. In some embodiments,a service is a program or a collection of programs that carry out aspecific function. In some embodiments, a service can be considered aserver. The memory can be a non-transitory computer-readable medium.

In some embodiments, the computer-readable storage devices, mediums, andmemories can include a cable or wireless signal containing a bit streamand the like. However, when mentioned, non-transitory computer-readablestorage media expressly exclude media such as energy, carrier signals,electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer-readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The executable computer instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, solid-state memory devices, flash memory, USB devices providedwith non-volatile memory, networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include servers,laptops, smartphones, small form factor personal computers, personaldigital assistants, and so on. The functionality described herein alsocan be embodied in peripherals or add-in cards. Such functionality canalso be implemented on a circuit board among different chips ordifferent processes executing in a single device, by way of furtherexample.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims.

What is claimed:
 1. A system comprising: one or more processors; and acomputer-readable medium comprising instructions stored therein, whichwhen executed by the one or more processors, cause the one or moreprocessors to perform operations comprising: receiving informationassociated with a status of one or more systems of an autonomousvehicle, wherein the status is detected by one or more sensors;determining that the status indicates a readiness of a passenger of theautonomous vehicle to initiate operation; and preparing the autonomousvehicle for initiation of operation in response to the determinationthat the status of the one or more systems indicates readiness of thepassenger.
 2. The system of claim 1, wherein the one or more processorsare further configured to perform operations comprising: selecting oneor more seat weight sensors from a plurality of AV sensors to check thestatus of a seatbelt; capturing, from the one or more seat weightsensors, a detection that a seat is occupied; determining that theseatbelt associated with the seat is fastened; and initiating operationof the autonomous vehicle based on the seatbelt being fastened.
 3. Thesystem of claim 1, wherein the one or more processors are furtherconfigured to perform operations comprising: selecting one or more imagesensors from a plurality of AV sensors to check the status of aseatbelt; capturing, from the image sensors, a detection that a seat isoccupied; determining that the seatbelt associated with the seat isfastened; and initiating operation of the autonomous vehicle based onthe seatbelt being fastened.
 4. The system of claim 1, wherein the oneor more processors are further configured to perform operationscomprising: selecting one or more door sensors from a plurality of AVsensors to check the status of a door of the autonomous vehicle;determining, from the one or more door sensors, that a door is properlyclosed; and initiating operation of the autonomous vehicle based on thedoor being properly closed.
 5. The system of claim 1, wherein theautonomous vehicle prompts the passenger to enact an action when thestatus is determined to indicate the passenger is not ready forautonomous vehicle operation.
 6. The system of claim 1, wherein theautonomous vehicle determines statuses of multiple systems and promptsthe passenger to enact all necessary actions at once.
 7. The system ofclaim 1, wherein the one or more processors are further configured toperform operations comprising: receiving information associated with abehavior of the passenger, wherein the behavior of the passenger isdetected by the one or more sensors; determining if the behavior of thepassenger is an indication of readiness of the passenger for theautonomous vehicle to initiate operation; and initiating the operationin response to the indication of the readiness of the passenger.
 8. Amethod comprising: receiving information associated with a status of oneor more systems of an autonomous vehicle, wherein the status is detectedby one or more sensors; determining that the status indicates areadiness of a passenger of the autonomous vehicle to initiateoperation; and preparing the autonomous vehicle for initiation ofoperation in response to the determination that the status of the one ormore systems indicates readiness of the passenger.
 9. The method ofclaim 8, comprising: selecting one or more seat weight sensors from aplurality of AV sensors to check the status of a seatbelt; capturing,from the one or more seat weight sensors, a detection that a seat isoccupied; determining that the seatbelt associated with the seat isfastened; and initiating operation of the autonomous vehicle based onthe seatbelt being fastened.
 10. The method of claim 8, comprising:selecting one or more image sensors from a plurality of AV sensors tocheck the status of a seatbelt; capturing, from the image sensors, adetection that a seat is occupied; determining that the seatbeltassociated with the seat is fastened; and initiating operation of theautonomous vehicle based on the seatbelt being fastened.
 11. The methodof claim 8, comprising: selecting one or more door sensors from aplurality of AV sensors to check the status of a door of the autonomousvehicle; determining, from the one or more door sensors, that a door isproperly closed; and initiating operation of the autonomous vehiclebased on the door being properly closed.
 12. The method of claim 8,wherein the autonomous vehicle prompts the passenger to enact an actionwhen the status is determined to indicate the passenger is not ready forautonomous vehicle operation.
 13. The method of claim 8, wherein theautonomous vehicle determines statuses of multiple systems and promptsthe passenger to enact all necessary actions at once.
 14. The method ofclaim 8, comprising: receiving information associated with a behavior ofthe passenger, wherein the behavior of the passenger is detected by theone or more sensors; determining if the behavior of the passenger is anindication of readiness of the passenger for the autonomous vehicle toinitiate operation; and initiating the operation in response to theindication of the readiness of the passenger.
 15. A non-transitorycomputer-readable medium comprising instructions stored thereon, theinstructions effective to cause at least one processor to: receiveinformation associated with a status of one or more systems of anautonomous vehicle, wherein the status is detected by one or moresensors; determine that the status indicates a readiness of a passengerof the autonomous vehicle to initiate operation; and prepare theautonomous vehicle for initiation of operation in response to thedetermination that the status of the one or more systems indicatesreadiness of the passenger.
 16. The non-transitory computer-readablemedium of claim 15, wherein the instructions further cause the at leastone processor to: select one or more seat weight sensors from aplurality of AV sensors to check the status of a seatbelt; capture, fromthe one or more seat weight sensors, a detection that a seat isoccupied; determine that the seatbelt associated with the seat isfastened; and initiate operation of the autonomous vehicle based on theseatbelt being fastened.
 17. The non-transitory computer-readable mediumof claim 15, wherein the instructions further cause the at least oneprocessor to: select one or more image sensors from a plurality of AVsensors to check the status of a seatbelt; capture, from the imagesensors, a detection that a seat is occupied; determine that theseatbelt associated with the seat is fastened; and initiate operation ofthe autonomous vehicle based on the seatbelt being fastened.
 18. Thenon-transitory computer-readable medium of claim 15, wherein theinstructions further cause the at least one processor to: select one ormore door sensors from a plurality of AV sensors to check the status ofa door of the autonomous vehicle; determine, from the one or more doorsensors, that a door is properly closed; and initiate operation of theautonomous vehicle based on the door being properly closed.
 19. Thenon-transitory computer-readable medium of claim 15, wherein theautonomous vehicle prompts the passenger to enact an action when thestatus is determined to indicate the passenger is not ready forautonomous vehicle operation.
 20. The non-transitory computer-readablemedium of claim 15, wherein the instructions further cause the at leastone processor to: receive information associated with a behavior of thepassenger, wherein the behavior of the passenger is detected by the oneor more sensors; determine if the behavior of the passenger is anindication of readiness of the passenger for the autonomous vehicle toinitiate operation; and initiate the operation in response to theindication of the readiness of the passenger.